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-qualification research experience. Relevant areas of research include computational chemistry, structural biology/bioinformatics, statistics, machine learning, computer science or mathematics. They will have a
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system planning, system modelling, multi-criteria decision analysis, data science, and machine learning. You will perform stakeholder engagement and on-the-ground data collection in LMIC contexts and
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Blavatnik School of Government ( https://ewada.ox.ac.uk ). It is essential that successful candidate would hold a relevant PhD/DPhil or being close to completion in computer science, machine learning, human
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integrated with the NiMARE (NMA) software project. To be considered you will hold a relevant PhD/Dphil in statistics, machine learning or similar area, together with relevant experience working with brain
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a PhD/DPhil or equivalent in a quantitative discipline such as computer science, statistics, machine learning, statistical or population genetics, or a related field. They should have experience in
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We are seeking a full-time Postdoctoral Research Associate in Machine Learning for Grid-Edge Flexibility to join the Power Systems Architecture Lab within the Department of Engineering Science
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projects. It is essential that you hold a PhD/DPhil in a quantitative or computer science related subject (e.g. Statistics, Machine Learning, Biostatistics, AI, Engineering), and have post-qualification
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Scientist to join the research group of Professor Stephanie Cragg on a discovery project in the field of striatal neurobiology. The ideal candidate will hold a PhD in a relevant area of neurobiology and
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, experience in bioinformatics, such as developing computational pipelines or applying advanced machine learning algorithms, and supervising student research would be desirable. Applications for this vacancy
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• Assist in IP protection and commercialisation activities Selection criteria: • PhD or equivalent experience in a relevant field • Experience with grant writing, IP management, and research